I want to chime in on Mike's comment about density of landmarking changing the
effect size. Nicolas Navarro and I did something similar in context of
quantitative genetics of mandible shape and came to a similar conclusion using
2D, 3D and 3D semi-landmarks sets on same dataset.

Navarro N, Maga AM. 2016. Does 3D Phenotyping Yield Substantial Insights in the
Genetics of the Mouse Mandible Shape? G3: Genes, Genomes, Genetics 6:1153–1163.
-----Original Message-----
From: Mike Collyer [mailto:mlcoll...@gmail.com]
Sent: Wednesday, May 31, 2017 7:43 AM
To: Lea Wolter <leawolter...@gmail.com>
Cc: MORPHMET <morphmet@morphometrics.org>
Subject: Re: [MORPHMET] number of landmarks and sample size
Dear Lea,
I see others have responded to your inquiry, already. I thought I would add an
additional perspective.
Your question about statistical significance requires asking a follow-up
question. What statistical methods would you intend to use to evaluate
“significance”? If you are worried about the number of landmarks, your concern
suggests you might be using parametric test statistics frequently associated
with MANOVA, like Wilks lambda or Pilai trace. Indeed, when using these
statistics and converting them to approximate F values, one must have many more
specimens than landmarks (more error degrees of freedom than shape variables,
to be more precise), if “significance” is to be inferred from probabilities
associated with F-distributions. Therefore, limiting the number of landmarks
might be a goal.
When using resampling procedures to conduct ANOVA, using fewer landmarks can
paradoxically decrease effect sizes, as an overly simplified definition of
shape becomes implied. We demonstrated this in our paper: Collyer, M.L., D.J.
Sekora, and D.C. Adams. 2015. A method for analysis of phenotypic change for
phenotypes described by high-dimensional data. Heredity. 115: 357-365. This is
consistent with Andrea’s comment about quality over quantity with the caveat
that limited quantity precludes quality. In other words, too few landmarks
translates to limited ability to discern shape differences, because the shape
compared is basic. In the paper, we used two separate landmark configurations:
one with few landmarks and the other with the same landmarks plus sliding
semilandmarks between fixed points, on different populations of fish. We found
that adding the semilandmarks increased the effect size for population
differences and sexual dimorphism. But if we constrained our analyses to
parametric MANOVA for our small samples, we would have to use the simpler
landmark configurations and live with the results.
I do not wish to suggest that adding more landmarks is better. Overkill is
certainly a concern. I would suggest though that statistical power would be
for me less of a concern than a proper characterization of the shape I wish to
compare among samples. If I suspect curvature is important but am afraid to
use (semi)landmarks that would allow me to assess the curvature differences
among groups, opting instead to use just the endpoints of a structure because I
am worried about statistical power, then I just allowed a statistical procedure
to take me away from the biologically relevant question I sought to address.
Andrea is correct that quality is better than quantity, but quantity can be a
burden in either direction (too few or too many). Additionally, statistical
power will vary among statistical methods. Reconsidering methods might be as
important as reconsidering landmarks configurations.
Regards!
Mike
> On May 4, 2017, at 5:19 AM, Lea Wolter <leawolter...@gmail.com> wrote:
>
> Hello everyone,
>
> I am new in the field of geometric morphometrics and have a question for my
> bachelor thesis.
>
> I am not sure how many landmarks I should use at most in regard to the sample
> size. I have a sample of about 22 individuals per population or maybe a bit
> less (using sternum and epigyne of spiders) with 5 populations.
> I have read a paper in which they use 18 landmarks with an even lower sample
> size (3 populations with 20 individuals, 1 with 10). But I have also heard
> that I should use twice as much individuals per population as land marks...
>
> Maybe there is some mathematical formula for it to know if it would be
> statistically significant? Could you recommend some paper?
>
> Because of the symmetry of the epigyne I am now thinking of using just one
> half of it for setting landmarks (so I get 5 instead of 9 landmarks). For the
> sternum I thought about 7 or 9 landmarks, so at most I would also get 18
> landmarks like in the paper.
>
> I would also like to use two type specimens in the analysis, but I have just
> this one individual per population... would it be totally nonesens in a
> statistical point of view?
>
> Thanks very much for your help!
>
> Best regards
> Lea
>
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